Is active commuting associated with metabolic syndrome in adults, adolescents, and children? a systematic review and meta-analysis
Bibliographic record
Abstract
Aims The prevalence of metabolic syndrome (MetS) is increasing annually across all age groups, raising the risk of morbidity, mortality, diabetes and cardiovascular disease in adults, adolescents, and children. Active commuting (AC) provides an opportunity to increase physical activity and reduce the MetS risk. The purpose of this study was to synthesize the available evidence on the prevalence of MetS and MetS risk factors in relation to AC vs non-active commuting among adults, adolescents, and children. Data synthesis PubMed and Web of Science databases were searched for studies investigating the relationship between MetS and AC, conducted following the PRISMA statement. The quality of the included studies was assessed using the Newcastle-Ottawa Scale and the AXIS tool. Meta-analyses were conducted using random-effects model. Eleven studies were included: seven studies in adults and one study in adolescents indicated that active commuters had lower odds of MetS prevalence compared to non-active commuters. This finding was supported by the ten studies included in the meta-analysis (Odds Ratio (OR)=0.88; 95% Confidence Interval (CI)= 0.83–0.94; p <0.001; Q =33.16; I 2 =72.86). Additionally, five studies in adults and one study in adolescents showed that active commuters had lower odds of abdominal obesity, a key MetS risk factor. This was corroborated by the six studies included in the meta-analysis (OR=0.72; 95%CI=0.61–0.84; p <0.001; Q =20.48; I 2 =75.59). Conclusion The prevalence of MetS and abdominal obesity seems to be lower among adults who engage in AC. However, generalization to younger populations is limited. Future intervention and longitudinal studies with objective and standardized measures are needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.032 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".